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A contactless charging system based on a circular coil configuration is presented for electric vehicles. An analytical model of the charging system is derived and used to investigate the effect of system dimensions on the system mutual inductance. The efficiency of the system is then calculated and used as a criterion to optimize the dimensions of transmitter and receiver coils in an uncompensated system, as well as series and parallel compensated systems. As a result, several design rules are presented. Following these rules, it is shown that significant improvement in the system efficiency is achieved by optimizing the coil dimensions while the length and weight of coils are kept constant. The performances of the optimized systems are evaluated using the 3-D finite-element method (FEM) and experiments. The FEM and experimental results are in good agreement, confirming the validity of the analytical model and the optimization approach.

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Partial Discharge (PD) is one of the symptoms of an electrical insulation problem, and its permanence can lead to the complete deterioration of the electrical insulation in high-voltage equipment such as power transformers. The acoustic emission (AE) method is a well-known technique used to detect and localize PD activity inside oil-filled transformers. However, the commercially available monitoring systems based on acoustic sensors still have a high cost. This paper analyses the ability of low-cost piezoelectric sensors to identify PDs within oil-filled power transformers. To this end, two types of low-cost piezoelectric sensors were fully investigated using time-domain, frequency-domain, and time-frequency analysis, separately. Thereafter, the effectiveness of these sensors for PD detection and monitoring was studied. A three-phase distribution transformer filled with oil was examined. PDs were produced inside an oil-immersed transformer by applying a high voltage over two copper electrodes, and the AE sensors were coupled to the housing of the transformer. By extracting typical features from the AE signals, the PD signals were differentiated from on-site noise and interference. The AE signals were analyzed using acoustic signal metrics such as peak value, energy criterion, and other statistical parameters. The obtained results indicated that the used low-cost piezoelectric sensors have the capability of PD monitoring within power transformers.